Designing Swarm-based Decentralised Systems: Requirements for Performance and Scalability

n the era of 5G and the upcoming 6G, current software stacks are ineffective when it comes to intelligent and fast decision-making, which necessitates the need for sustainable yet performant and scalable solutions. A significant amount of research has been done in this area, but an end-to-end solution was lacking. In this scope, we identify that we need a novel software stack which can handle the growing need for a vast amount of data generation with the help of the cloud-edge continuum, swarm programmability, along with secure deployments of applications. In this context, we propose OASEES, an architectural framework for a decentralised AI/ML computing stack that unifies diverse computing resources, peer-to-peer coordination protocols, and secure middleware. Our design outlines modular different compute infrastructures(CPUs, GPUs, TPUs and custom ASICs) orchestrated by a lightweight container-based runtime and governed by a blockchain-enabled tamper-proof data storage, decentralised coordination (decentralised autonomous organisation, voting, etc) to facilitate transparent discovery, allocation, and incentivization. We also propose a detailed performance and scalability metrics framework covering latency, throughput, resource utilisation, and cost-per-inference, intended as the foundation of subsequent evaluations.